Then, it suffices to estimate \(b_i\)  for each \(i\in [P]\) , where the Indyk-Woodruff sketching technique can be used to approximate the vector. At the \(i\) -th layer, each coordinate of \(v\)  is sampled with probability \(P/b_i\) , and then the algorithm identifies the \(\ell _2\) -heavy-hitters of the sampled vector. [1]} gave a criterion for identifying the important layers, whose heavy-hitter coordinates in the corresponding sampled vectors, is enough to recover the entire symmetric norm \(\Vert  v \Vert _{\mathrm {sym}}\) .
